Unsupervised segmentation of continuous genomic data

Abstract

The advent of high-density, high-volume genomic data has created the
need for tools to summarize large datasets at multiple scales. HMMSeg
is a command-line utility for the scale-specific segmentation of
continuous genomic data using hidden Markov models
(HMMs). Scale-specificity is achieved by an optional wavelet-based
smoothing operation. HMMSeg is capable of handling multiple datasets
simultaneously, rendering it ideal for integrative analysis of
expression, phylogenetic, and functional genomic data.